当我运行代码时，model.fit 最终返回一个错误：IndexError: list index out of range。
数据集：https://drive.google.com/file/d/11_dvun93KNdK9WrMtNzSB5HDBCgtq8qG/view?usp=sharing
# importing and cleaning the data
import pandas as pd
import numpy as np
import pandas as pd
import re
import nltk
import string
dataset = pd.read_csv("car_prices.csv")
dataset.pop('vin')
dataset.pop('mmr')
dataset.pop('year')
dataset.pop('odometer')
dataset.pop('condition')
dataset.pop('transmission')
dataset.pop('saledate')
dataset.pop('color')
dataset.pop('interior')
dataset = dataset.dropna(axis=0)
labels = dataset.iloc[:,0:5].values
labels = str(labels)
data = dataset.iloc[:,6].values
print(labels)
MODEL = "https://tfhub.dev/google/universal-sentence-encoder-large/5"
hub_layer = hub.KerasLayer(MODEL, output_shape=[512], input_shape=[1], trainable=True, dtype="string")
model = Sequential()
model.add(hub_layer)
model.add(Dense(1))
model.compile(loss='categorical_crossentropy', optimizer='SGD', metrics=['accuracy'])
data = np.array(np.array(data))
labels = np.array(np.array(labels))
model.fit(data, labels, epochs=2)